Quantifying the relationship between SARS-CoV-2 viral load and infectiousness
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Abstract
The relationship between SARS-CoV-2 viral load and infectiousness is poorly known. Using data from a cohort of cases and high-risk contacts, we reconstructed viral load at the time of contact and inferred the probability of infection. The effect of viral load was larger in household contacts than in non-household contacts, with a transmission probability as large as 48% when the viral load was greater than 10 10 copies per mL. The transmission probability peaked at symptom onset, with a mean probability of transmission of 29%, with large individual variations. The model also projects the effects of variants on disease transmission. Based on the current knowledge that viral load is increased by two- to eightfold with variants of concern and assuming no changes in the pattern of contacts across variants, the model predicts that larger viral load levels could lead to a relative increase in the probability of transmission of 24% to 58% in household contacts, and of 15% to 39% in non-household contacts.
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SciScore for 10.1101/2021.05.07.21256341: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources All simulations were performed using the Simulx package on R.3.6.0. Simulxsuggested: (Simulx, RRID:SCR_000486)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our study has some important limitations that need to be acknowledged. First, the reporting of high-risk contacts is partial and remains prone to various reporting biases. One of them is the fact that at the time …
SciScore for 10.1101/2021.05.07.21256341: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources All simulations were performed using the Simulx package on R.3.6.0. Simulxsuggested: (Simulx, RRID:SCR_000486)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our study has some important limitations that need to be acknowledged. First, the reporting of high-risk contacts is partial and remains prone to various reporting biases. One of them is the fact that at the time where the study was conducted, there was no firm evidence of the role of pre-symptomatic transmission. This could explain why in our study a large number of high-risk household contact were reported to occur the day of symptom onset. It is also possible that several of the household contacts were not unique and occurred multiple times. Because we had no information on these contacts, we did not conduct specific analyses on repeated contacts, but it is something that future epidemiological studies will need to investigate. Another limitation is that we had no genomic data to ensure that infection observed in contact individuals results from an infection by the index case. In most infected contacts, we also did not have data on the time of symptom onset, which prevented us from detecting infections unlikely related to the contact identified in our study. However, the temporality of symptoms would not be sufficient to bring a decisive information on the infection event. Indeed, the study was conducted during the first epidemic wave in Spain, where most individuals, including in hospital settings, had not yet applied social distancing and masking, causing dozens of thousands of individuals infected every day. Both the possibility of repeated contacts in household and inf...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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